2023
DOI: 10.32517/0234-0453-2023-38-3-31-41
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Predicting academic performance in a course by universal features of LMS Moodle digital footprint

Abstract: Student retention prediction is one of the most important problems of learning analytics. In the global scope research on the topic for higher education is rather extensive, there are cases of successful implementation of education support services in universities. The literature analysis shows of the growing interest in this problem in the Russian scientific and pedagogical community. At the same time, the specifics of Russian education does not allow direct transfer of foreign experience into the domestic ed… Show more

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Cited by 4 publications
(3 citation statements)
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“…Based on the LMS Moodle activity data, a student digital footprint was created, which contains current learning characteristics of a student within the electronic course: the grade points, clicking internal links, time spent on course pages, etc. [48,49].…”
Section: Digital Profile Of a Studentmentioning
confidence: 99%
See 1 more Smart Citation
“…Based on the LMS Moodle activity data, a student digital footprint was created, which contains current learning characteristics of a student within the electronic course: the grade points, clicking internal links, time spent on course pages, etc. [48,49].…”
Section: Digital Profile Of a Studentmentioning
confidence: 99%
“…In particular, it is highly desirable to identify in which specific courses the difficulties have arisen, i.e., to solve the task of predicting academic success for each course. Such models for predicting success based on digital footprint data in the electronic educational environment has been previously developed and tested in the educational process at SibFU [47,49].…”
Section: Hybrid Approach To Forecasting the Success Of Learningmentioning
confidence: 99%
“…Such systems can be implemented at various levels of educational hierarchy. In references [14,16], learning analytics (LA) solutions were executed at the course level, whereas in references [17,18], the authors presented a review of university-wide learning support systems.…”
Section: An Overview Of Existing Learning Analytics Tools and Practicesmentioning
confidence: 99%